As reviewed in [1]} and [2]}, modern quantum algorithms for optimization on NISQ devices have generalized significantly the original structure of the QAOA circuitry.
In this paper, we have presented a variation that combines the hardware-efficient spirit of Variational Quantum Eigensolvers with the advanced mixers of the Quantum Alternating Operator Ansatz and the guidance from inclusion of operators derived from the cost function without increasing the number of parameters that need to be optimized.
Our numerical results indicate that the mixer-phaser ansatz QAMPA is a compelling choice among NISQ era quantum options;
we expect these ideas can be ported beyond the
\(\mathtt {WeightedMaxCutGSP}\)  problem, to provide compilation advantages to a multitude of other hard-constrained combinatorial optimization problems that require advanced mixers. Multiple questions however remain in order to bridge the gap from proof-of-principles to real-world implementation. We list here few avenues of research towards the goal of deploying a QAMPA solver in a quantum processor, before concluding with some more general thoughts on research directions.
